The most common issues are unclear scope, fragmented ownership, weak visibility into where AI is being used, policy language that is disconnected from operations, poor documentation discipline, and governance processes that cannot be explained clearly with evidence. Another common problem is leaving AI governance too late, which creates rework when customer due diligence, internal oversight, or certification preparation begins.